Public response to government alerts saves lives during Russian invasion of Ukraine.

War is the cause of tremendous human suffering. To reduce such harm, governments have developed tools to alert civilians of imminent threats. Whether these systems are effective remains largely unknown. We study the introduction of an innovative smartphone application that notifies civilians of impending military operations developed in coordination with the Ukrainian government after the Russian invasion. We leverage quasi-experimental variation in the timing of more than 3,000 alerts to study civilian sheltering behavior, using high-frequency geolocation pings tied to 17 million mobile devices, 60% of the connected population in Ukraine. We find that, overall, civilians respond sharply to alerts, quickly seeking shelter. These rapid postalert changes in population movement attenuate over time, however, in a manner that cannot be explained by adaptive sheltering behavior or calibration to the signal quality of alerts. Responsiveness is weakest when civilians have been living under an extended state of emergency, consistent with the presence of an alert fatigue effect. Our results suggest that 35 to 45% of observed civilian casualties were avoided because of public responsiveness to the messaging system. Importantly, an additional 8 to 15% of civilian casualties observed during the later periods of the conflict could have been avoided with sustained public responsiveness to government alerts. We provide evidence that increasing civilians' risk salience through targeted government messaging can increase responsiveness, suggesting a potential policy lever for sustaining public engagement during prolonged episodes of conflict.

Poverty and economic dislocation reduce compliance with COVID-19 shelter-in-place protocols.

Shelter-in-place ordinances were the first wide-spread policy measures aimed to mitigate the spread of COVID-19. Compliance with shelter-in-place directives is individually costly and requires behavioral changes across diverse sub-populations. Leveraging county-day measures on population movement derived from cellphone location data and the staggered introduction of local mandates, we find that economic factors have played an important role in determining the level of compliance with local shelter-in-place ordinances in the US. Specifically, residents of low income areas complied with shelter-in-place ordinances less than their counterparts in areas with stronger economic endowments, even after accounting for potential confounding factors including partisanship, population density, exposure to recent trade disputes, unemployment, and other factors. Novel results on the local impact of the 2020 CARES Act suggest stimulus transfers that addressed economic dislocation caused by the COVID-19 pandemic significantly increased social distancing.

Science skepticism reduced compliance with COVID-19 shelter-in-place policies in the United States.

Physical distancing reduces transmission risks and slows the spread of COVID-19. Yet compliance with shelter-in-place policies issued by local and regional governments in the United States was uneven and may have been influenced by science skepticism and attitudes towards topics of scientific consensus. Using county-day measures of physical distancing derived from cell phone location data, we demonstrate that the proportion of people who stayed at home after shelter-in-place policies went into effect in March and April 2020 in the United States was significantly lower in counties with a high concentration of science skeptics. These results are robust to controlling for other potential drivers of differential physical distancing, such as political partisanship, income, education and COVID severity. Our findings suggest that public health interventions that take local attitudes towards science into account in their messaging may be more effective.

Political and environmental risks influence migration and human smuggling across the Mediterranean Sea.

Since 2007 the number of refugees fleeing conflict and violence has doubled to more than 25 million. We leverage high frequency data on migration, sea conditions, and riots to investigate how political and environmental risks influence migration and human smuggling across the Mediterranean Sea. We report results from two observational studies. A high frequency time-series study demonstrates that risks alter migration patterns. An event study design demonstrates the effectiveness of a policy intervention that targeted Libyan militias engaged in human smuggling. The results highlight the important role of environmental and political risks in transit countries and their implications for migration and human smuggling.